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Advisor(s)
Abstract(s)
This paper presents a novel approach for creating
virtual LiDAR scanners through the active segmentation
of point clouds. The method employs top-view point cloud
segmentation in virtual LiDAR sensors that can be applied to
the intelligent behavior of autonomous agents. Segmentation
is correlated with the visual tracking of the agent for localization
in the environmentand point cloud. Virtual LiDARsensors
with different characteristicsand positions can then be generated.
Thismethod is referred to as the DepthLiDAR approach,
and is rigorously evaluated to quantify its performance and
determine its advantages and limitations. An extensive set
of experiments is conducted using real and virtual LiDAR
sensors to compare both approaches. The objective is to
propose a novel method to incorporate spatial perception in warehouses, aiming to achieve Industry 4.0. Thus, it is
tested in a low-scale warehouse to incorporate realistic features. The analysis of the experiments shows a measurement
improvement of 52.24% compared to the conventional LiDAR.
Description
Keywords
Virtual sensors LIDAR Point cloud Active segmentation Industry 4.0.
Citation
Limeira, Marcelo; Piardi, Luis; Kalempa, Vivian Cremer; Leitão, Paulo; Oliveira, Andre Schneider (2021). DepthLiDAR: active segmentation of environment depth map into mobile sensors. IEEE Sensors Journal. ISSN 1558-1748. 21:17, p. 19047-19057